Protein Interactions and Protein Conformation in Aging and Disease (6 of 11)

衰老和疾病中的蛋白质相互作用和蛋白质构象（11 中的 6）

• 批准号: 7498021
• 负责人: ROBERT E HUGHES
• 金额: $ 47.58万
• 依托单位: BUCK INSTITUTE FOR RESEARCH ON AGING
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-09-28 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7498021
• 关键词: Age; Aging; Animal Model; Bioinformatics; Biological Assay; Biological Models; Brain; Caenorhabditis elegans; Cells; Data; Data Set; Disease; Genes; Genetic Models; Human; Informatics; Invertebrates; Kinetics; Life; Longevity; Maps; Methods; Mining; Molecular Conformation; Mus; Muscle; Mutate; Nematoda; Nerve Degeneration; Neurological Models; Orthologous Gene; Process; Protein Conformation; Proteins; Proteome; Proteomics; Role; Solubility; Testing; Time; Tissues; Two-Hybrid System Techniques; Yeasts; age related; base; brain tissue; longevity gene; mouse model; mutant; nervous system disorder; novel; protein protein interaction

We propose to define and characterize protein interactions and protein conformational states relevant to aging and disease processes. A starting point for the interaction studies will be a large protein interaction network involving human orthologs of proteins known to increase longevity when mutated in models systems of aging. This scale-free network, generated using high throughput yeast two-hybrid methods, includes 2,172 human proteins interacting with 165 known longevity proteins in 3,219 highly interconnected unique binary pairs. Because of their interaction with known longevity proteins, these 2,172 are considered to be novel candidate longevity proteins. Analysis of genes encoding known and candidate longevity proteins show that they are highly enriched for genes whose expression changes during human aging (according to microarray data generated from young and old human muscle tissue). The "longevity interactome" will be mined using bioinformatic methods and novel longevity genes derived from the network will be validated using C. elegans life span assays. A complementary approach to discovering novel proteins involved in aging will be to use mass spectrometrybased proteomic methods to discover proteins that become insoluble over time, in aging and disease. We will determine the content of the SDS insoluble fraction of the proteome in aging model organisms, aging mouse tissues and brains from mouse models of neurological disease. Proteins found to partition into insoluble states during aging and/or disease will be investigated further for possible functional roles in these processes using invertebrate and mouse models. Specific Aim 1. To discover and characterize novel genes relevant to longevity using an aging protein interaction network. We will mine an existing protein interaction network to identify novel protein involved in aging and longevity. Candidate proteins will be prioritized using informatic methods, compared to age-specific microarray datasets and validated experimentally in model organisms of aging. Proteins validated as having roles in aging will be studied further using MS-based proteomic methods. Specific Aim 2. To develop proteome-scale maps of age-dependent changes in protein solubility. We will use MS-based methods to determine which proteins become insoluble in an age-dependent manner. This will be done in aging yeast, nematodes and tissues from aging and diseased mice (e.g. brain and muscle). Kinetics of changes in protein solubility will be tested in long-lived mutant yeast and nematodes and also in genetic models of late-onset neurodegeneration (e:g. AD, HD and PD mouse models). Proteins shown to be susceptible to age-dependent and disease-dependent insolubility will be functionally characterized in appropriate invertebrate, cell-based and mouse models of aging and disease.

我们建议定义和表征蛋白质相互作用和蛋白质构象状态相关的